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Network Automation with AI

Course Code:

Detalles del curso

Descripción

Key Topics Covered

  • Foundations of closed-loop automation, including the Monitor–Analyse–Decide–Act model and its role in improving service reliability, efficiency, and SLA performance across network domains
  • Telemetry and real-time observability, covering data collection from multi-domain sources, streaming analytics, and integration with assurance systems
  • Analytics and decision-making frameworks, including rule-based and AI-driven policy engines for SLA monitoring, predictive analysis, and automated decision triggers
  • Automated orchestration and remediation actions, enabling scaling, rerouting, reconfiguration, and fault recovery across RAN, Core, Transport, and Cloud
  • End-to-end service assurance integration, including KPI monitoring, SLA enforcement, incident automation, and alignment with operational processes

Learning Outcomes

  • Apply closed‑loop automation frameworks (monitor → analyse → decide → act)
  • Identify relevant telemetry/KPI sources for real‑time decisions
  • Explain interplay between analytics engines and orchestration layers
  • Understand assisted vs full closed‑loop implementation models."

Target Audience

  • Network automation engineers
  • AI/analytics engineers supporting network assurance
  • OSS platform architects
    Operations teams responsible for service assurance and performance

Detalles del curso

Forma del producto

Key Topics Covered Foundations of closed-loop automation, including the Monitor–Analyse–Decide–Act model and its role in improving service reliability, efficiency, and... Leer más...

Schedule Closed Course

Duration:
Price: £POA (up to 12 Delegates)

Cada curso incluye:

  • Impartido por expertos en la materia con décadas de experiencia en la industria.
  • Disponible para impartición en aula o vía aula virtual.
  • El aula virtual ofrece la misma experiencia de aprendizaje interactiva y atractiva que la capacitación en el aula presencial.
  • Disponible como programa de formación interna cerrado. Para más información, contacte con info@wraycastle.com .

Descripción

Key Topics Covered

  • Foundations of closed-loop automation, including the Monitor–Analyse–Decide–Act model and its role in improving service reliability, efficiency, and SLA performance across network domains
  • Telemetry and real-time observability, covering data collection from multi-domain sources, streaming analytics, and integration with assurance systems
  • Analytics and decision-making frameworks, including rule-based and AI-driven policy engines for SLA monitoring, predictive analysis, and automated decision triggers
  • Automated orchestration and remediation actions, enabling scaling, rerouting, reconfiguration, and fault recovery across RAN, Core, Transport, and Cloud
  • End-to-end service assurance integration, including KPI monitoring, SLA enforcement, incident automation, and alignment with operational processes

Learning Outcomes

  • Apply closed‑loop automation frameworks (monitor → analyse → decide → act)
  • Identify relevant telemetry/KPI sources for real‑time decisions
  • Explain interplay between analytics engines and orchestration layers
  • Understand assisted vs full closed‑loop implementation models."

Target Audience

  • Network automation engineers
  • AI/analytics engineers supporting network assurance
  • OSS platform architects
    Operations teams responsible for service assurance and performance

Nuestros clientes y socios

  • UIC Rail Academy
  • IEEE
  • TCCA
  • UKTIN
  • DB
  • Scotish Fire
  • MTN
  • All Points Fibre
  • Department of Defence

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